The present disclosure relates to coding of image content, for example, in still-image and motion picture image data.
Image coding generally refers to compression of image data to achieve bandwidth compression. Typically, image coding exploits spatial and, in the case of motion picture content, temporal redundancies in data. When redundancies are identified, redundant content may be coded differentially with respect to other, previously-coded content, which achieves compression. Oftentimes, source image data is partitioned into spatial regions, called “pixel blocks” for convenience, and searches for redundancies are performed on a pixel block by pixel block basis.
Still other compression operations may be performed. In one technique, pixel values within pixel blocks may be converted to frequency coefficients by, for example, a discrete cosine transform or a discrete sine transform. These coefficients may undergo quantization and entropy coding. Quantization often incurs data losses that cannot be recovered during inverse quantization operations. In such applications, decoding operations are likely to generate reconstructed image data that resembles source image data with some errors. In many cases, the errors may be perceptible to human viewers as errors, called “artifacts” for convenience.
Coding protocols have been developed to adaptively select the sizes of the pixel blocks that will be coded. Improper selection of pixel block sizes can be disadvantageous and create artifacts that are easily perceived by viewers.